Survival/Analysis of time to event data

Overview

Survival analysis studies the amount of time it takes before a particular event of interest occurs. It plays a pivotal role in statistical modeling, especially in business, medicine, biology and reliability studies where time-to-event data is fundamental.

What types of questions can be answered with survival analysis?

What is the probability of experiencing an adverse outcome from a specific cause by a given time?
Does a specific intervention reduce adverse outcomes for all causes or just for specific ones?
On average, how long after an intervention/treatment/procedure do different groups experience some specific adverse outcome?

What types of models can we implement at oores Analytics?

Kaplan-Meier survival curve with confidence intervals and confidence bands,
Wilcoxon, log-rank test,
Kernel-Smoothed Hazard Estimator,
Cox Proportional Hazards Models,
Competing Risks Analysis

At oores Analytics, we have the tools necessary to analyze and interpret time-to-event data within a rigorous stochastic framework. Talk to us and see how we can help you harness the power of your data, translating same into real-world scenarios, and thus enable you make data-driven decisions!

Case studies

See our case studies about data analyst case

Overview

Survival analysis studies the amount of time it takes before a particular event of interest occurs. It plays a pivotal role in statistical modeling, especially in business, medicine, biology and reliability studies where time-to-event data is fundamental.

What types of questions can be answered with survival analysis?

What is the probability of experiencing an adverse outcome from a specific cause by a given time?
Does a specific intervention reduce adverse outcomes for all causes or just for specific ones?
On average, how long after an intervention/treatment/procedure do different groups experience some specific adverse outcome?

What types of models can we implement at oores Analytics?

Kaplan-Meier survival curve with confidence intervals and confidence bands,
Wilcoxon, log-rank test,
Kernel-Smoothed Hazard Estimator,
Cox Proportional Hazards Models,
Competing Risks Analysis

At oores Analytics, we have the tools necessary to analyze and interpret time-to-event data within a rigorous stochastic framework. Talk to us and see how we can help you harness the power of your data, translating same into real-world scenarios, and thus enable you make data-driven decisions!